Machine Learning and Data-Driven Techniques for the Control of Smart Power Generation Systems:An Uncertainty Handling Perspective

Due to growing concerns regarding climate change and environmental protection,smart power generation has become essential for the economical and safe operation of both conventional thermal power plants and sustainable energy.Traditional first-principle model-based methods are becoming insufficient when faced with the ever-growing system scale and its various uncertainties.The burgeoning era of machine learning(ML)and data-driven control(DDC)techniques promises an improved alternative to these outdated methods.This paper reviews typical applications of ML and DDC at the level of monitoring,control,optimization,and fault detection of power generation systems,with a particular focus on uncovering how these methods can function in evaluating,counteracting,or withstanding the effects of the associated uncertainties.A holistic view is provided on the control techniques of smart power generation,from the regulation level to the planning level.The benefits of ML and DDC techniques are accordingly interpreted in terms of visibility,maneuverability,flexibility,profitability,and safety(abbreviated as the“5-TYs”),respectively.Finally,an outlook on future research and applications is presented.

Mobile power generation system based on biomass gasifcation

Disaster-hit and/or un-electrifed remote areas usually have electricity accessibility issues and an abundance of plant-derived debris and wood from destroyed wooden structures;this can be potentially addressed by employing a decentralized ultrasmall biomass-fed gasifcation power generating system.This paper presents an assessment of the technical viability of an ultra-small gasifcation system that utilizes densifed carbonized wood pellets/briquettes.The setup was run continuously for 100 h.A variety of biomass was densifed and carbonized by harnessing fugitive heat sources before charging into the reactor.Carbonized briquettes and furnished blends exhibited inferior gasifcation performance compared to the carbonized pellets.In the absence of tar blockage problems,steady-state conditions were achieved when pre-treated feedstock was used.Under steady-state conditions for carbonized pellets gasifcation operated at an equivalence ratio of 0.32,cold gas efciency and carbon conversion achieved 49.2%and 70.5%,respectively.Overall efciency and maximum power output of 20.3%and 21 kW were realised,respectively.It was found that the system could keep stable while the low heating valve of syngas was over 4 MJ/m^(3)on condition that avoiding tar blocking issues.The results indicate that the proposed compact ultra-small power generation system is a technically feasible approach to remedy power shortage challenge.In addition,process simulation considering carbonized wood gasifcation combined power generation was formulated to produce syngas and electricity.Woody pellets with the fow rate of 20 kg/h could generate a 15.18 kW power at the air fow rate of 40 Nm^(3)/h,which is in a good agreement with 15 kW in the 100 h operation.It is indicated that the gasifcation combined power generation cycle simulated by Aspen simulator could achieve reliable data to assist the complicated experiment operation.

Study and performance test of 10 kW molten carbonate fuel cell power generation system

The use of high-temperature fuel cells as a power technology can improve the efficiency of electricity generation and achieve near-zero emissions of carbon dioxide.This work explores the performance of a 10 kW high-temperature molten carbonate fuel cell.The key materials of a single cell were characterized and analyzed using X-ray diffraction and scanning electron microscopy.The results show that the pore size of the key electrode material is 6.5 lm and the matrix material is a-LiAlO_(2).Experimentally,the open circuit voltage of the single cell was found to be 1.23 V.The current density was greater than 100 mA/cm^(2)at an operating voltage of 0.7 V.The 10 kW fuel cell stack comprised 80 single fuel cells with a total area of 2000 cm^(2)and achieved an open circuit voltage of greater than 85 V.The fuel cell stack power and current density could reach 11.7 kW and 104.5 mA/cm2 at an operating voltage of 56 V.The influence and long-term stable operation of the stack were also analyzed and discussed.The successful operation of a 10 kW high-temperature fuel cell promotes the large-scale use of fuel cells and provides a research basis for future investigations of fuel cell capacity enhancement and distributed generation in China.

Multi-objective optimization and evaluation of supercritical CO_(2) Brayton cycle for nuclear power generation

The supercritical CO_(2) Brayton cycle is considered a promising energy conversion system for Generation IV reactors for its simple layout,compact structure,and high cycle efficiency.Mathematical models of four Brayton cycle layouts are developed in this study for different reactors to reduce the cost and increase the thermohydraulic performance of nuclear power generation to promote the commercialization of nuclear energy.Parametric analysis,multi-objective optimizations,and four decision-making methods are applied to obtain each Brayton scheme’s optimal thermohydraulic and economic indexes.Results show that for the same design thermal power scale of reactors,the higher the core’s exit temperature,the better the Brayton cycle’s thermo-economic performance.Among the four-cycle layouts,the recompression cycle(RC)has the best overall performance,followed by the simple recuperation cycle(SR)and the intercooling cycle(IC),and the worst is the reheating cycle(RH).However,RH has the lowest total cost of investment(C_(tot))of$1619.85 million,and IC has the lowest levelized cost of energy(LCOE)of 0.012$/(kWh).The nuclear Brayton cycle system’s overall performance has been improved due to optimization.The performance of the molten salt reactor combined with the intercooling cycle(MSR-IC)scheme has the greatest improvement,with the net output power(W_(net)),thermal efficiencyη_(t),and exergy efficiency(η_(e))improved by 8.58%,8.58%,and 11.21%,respectively.The performance of the lead-cooled fast reactor combined with the simple recuperation cycle scheme was optimized to increase C_(tot) by 27.78%.In comparison,the internal rate of return(IRR)increased by only 7.8%,which is not friendly to investors with limited funds.For the nuclear Brayton cycle,the molten salt reactor combined with the recompression cycle scheme should receive priority,and the gas-cooled fast reactor combined with the reheating cycle scheme should be considered carefully.

Research on the MPPT of Photovoltaic Power Generation Based on Improved WOA and P&O under Partial Shading Conditions

Partial shading conditions(PSCs)caused by uneven illumination become one of the most common problems in photovoltaic(PV)systems,which can make the PV power-voltage(P-V)characteristics curve show multi-peaks.Traditional maximum power point tracking(MPPT)methods have shortcomings in tracking to the global maximum power point(GMPP),resulting in a dramatic decrease in output power.In order to solve the above problems,intelligent algorithms are used in MPPT.However,the existing intelligent algorithms have some disadvantages,such as slow convergence speed and large search oscillation.Therefore,an improved whale algorithm(IWOA)combined with the P&O(IWOA-P&O)is proposed for the MPPT of PV power generation in this paper.Firstly,IWOA is used to track the range interval of the GMPP,and then P&O is used to accurately find the MPP in that interval.Compared with other algorithms,simulation results show that this method has an average tracking efficiency of 99.79%and an average tracking time of 0.16 s when tracking GMPP.Finally,experimental verification is conducted,and the results show that the proposed algorithm has better MPPT performance compared to popular particle swarm optimization(PSO)and PSO-P&O algorithms.

Comprehensive Benefit Evaluation of SZ Distributed Photovoltaic Power Generation Project Based on AHP-Matter-Element Extension Model

With the introduction of the“dual carbon goals,”there has been a robust development of distributed photovoltaic power generation projects in the promotion of their construction.As part of this initiative,a comprehensive and systematic analysis has been conducted to study the overall benefits of photovoltaic power generation projects.The evaluation process encompasses economic,technical,environmental,and social aspects,providing corresponding analysis methods and data references.Furthermore,targeted countermeasures and suggestions are proposed,signifying the research’s importance for the construction and development of subsequent distributed photovoltaic power generation projects.

Dynamic and Power Generation Features of A Wind-Wave Hybrid System Consisting of A Spar-Type Wind Turbine and An Annular Wave Energy Converter in Irregular Waves

Combining wave energy converters(WECs)with floating offshore wind turbines proves a potential strategy to achieve better use of marine renewable energy.The full coupling investigation on the dynamic and power generation features of the hybrid systems under operational sea states is necessary but limited by numerical simulation tools.Here an aero-hydro-servo-elastic coupling numerical tool is developed and applied to investigate the motion,mooring tension,and energy conversion performance of a hybrid system consisting of a spar-type floating wind turbine and an annular wave energy converter.Results show that the addition of the WEC has no significant negative effect on the dynamic performance of the platform and even enhances the rotational stability of the platform.For surge and pitch motion,the peak of the spectra is originated from the dominating wave component,whereas for the heave motion,the peak of the spectrum is the superposed effect of the dominating wave component and the resonance of the system.The addition of the annular WEC can slightly improve the wind power by making the rotor to be in a better position to face the incoming wind and provide considerable wave energy production,which can compensate for the downtime of the offshore wind.

On the State-dependent Switched Energy Functions of DFIG-based Wind Power Generation Systems

This paper proposes a novel state-dependent switched energy function(SdSEF)for general nonlinear autonomous systems,and constructs an SdSEF for doubly-fed induction generator(DFIG)-based wind power generation systems(WPGSs).Different from the conventional energy function,SdSEF is a piece-wise continuous function,and it satisfies the conditions of conventional energy functions on each of its continuous segments.SdSEF is designed to bridge the gap between the well-developed energy function theory and the description of system energy of complex nonlinear systems,such as power electronics converter systems.The stability criterion of nonlinear autonomous systems is investigated with SdSEF,and mathematical proof is presented.The SdSEF of a typical DFIGbased WPGS is simulated in the whole processes of a grid fault and fault recovery.Simulation results verify the negativeness of the derivative of each continuous segment of the SdSEF.

Application of a simplified Grey Wolf optimization technique for adaptive fuzzy PID controller design for frequency regulation of a distributed power generation system

A Simplified Grey Wolf Optimizer(SGWO)is suggested for resolving optimization tasks.The simplification in the original Grey Wolf Optimizer(GWO)method is introduced by ignoring the worst category wolves while giving priority to the better wolves during the search process.The advantage of the presented SGWO over GWO is a better solution taking less execution time and is demonstrated by taking unimodal,multimodal,and fixed dimension test functions.The results are also contrasted to the Gravitational Search Algorithm,the Particle Swarm Optimization,and the Sine Cosine Algorithm and this shows the superiority of the proposed SGWO technique.Practical application in a Distributed Power Generation System(DPGS)with energy storage is then considered by designing an Adaptive Fuzzy PID(AFPID)controller using the suggested SGWO method for frequency control.The DPGS contains renewable generation such as photovoltaic,wind,and storage elements such as battery and flywheel,in addition to plug-in electric vehicles.It is demonstrated that the SGWO method is superior to the GWO method in the optimal controller design task.It is also seen that SGWO based AFPID controller is highly efficacious in regulating the frequency compared to the standard PID controller.A sensitivity study is also performed to examine the impact of the unpredictability in the parameters of the investigated system on system performance.Finally,the novelty of the paper is demonstrated by comparing with the existing publications in an extensively used two-area test system.

Model predictive control of grid-connected PV power generation system considering optimal MPPT control of PV modules

Because of system constraints caused by the external environment and grid faults,the conventional maximum power point tracking(MPPT)and inverter control methods of a PV power generation system cannot achieve optimal power output.They can also lead to misjudgments and poor dynamic performance.To address these issues,this paper proposes a new MPPT method of PV modules based on model predictive control(MPC)and a finite control set model predictive current control(FCS-MPCC)of an inverter.Using the identification model of PV arrays,the module-based MPC controller is designed,and maximum output power is achieved by coordinating the optimal combination of spectral wavelength and module temperature.An FCS-MPCC algorithm is then designed to predict the inverter current under different voltage vectors,the optimal voltage vector is selected according to the optimal value function,and the corresponding optimal switching state is applied to power semiconductor devices of the inverter.The MPPT performance of the MPC controller and the responses of the inverter under different constraints are verified,and the steady-state and dynamic control effects of the inverter using FCS-MPCC are compared with the traditional feedforward decoupling PI control in Matlab/Simulink.The results show that MPC has better tracking performance under constraints,and the system has faster and more accurate dynamic response and flexibility than conventional PI control.

Biomass energy cost and feasibility of gasifier based biomass power generation system

The present research work has been carried out on biomass based on 10 kW capacity gasifier power generation system installed at College of Agricultural Engineering and Technology,Dr.Panjabrao Deshmukh Agricultural University(Dr.PDKV),Akola Maharashtra,India.The main objectives were to evaluate various costs and benefits involved in the power generation system.The costs of energy per unit were calculated for the first year of operation.The economics of gasifier based power generation system and thereby the feasibility of the system was examined by estimating per unit cost,Net Present Value(NPV),Benefit Cost Ratio(BCR),Internal Rate of Return(IRR)and payback period.The discount cash flow method was used to find out the IRR.In the present analysis,three costs viz.,installed capital cost,operation and maintenance cost,and levelised replacement cost were examined for the evaluation of the power generation per unit.Discount rate on investment in case of subsidy(Case I)and in case without subsidy(Case II)for installation cost of system was considered as 12.75%.The BCR comes in Case I for operating duration of 22 h,20 h,and 16 h are 1.24,1.18,and 1.13,respectively.Similarly for Case II BCR comes 1.44,1.38,and 2.39.The IRR comes in Case I for operating duration of 22 h,20 h,and 16 h are 26%,22%,and 19%,respectively.Similarly for Case II,IRR comes 52%,44%,and 39%for operating duration of 22 h,20 h,and 16 h,respectively.The payback period in the present analysis was worked out.The payback period for biomass based gasifier power generation system was observed to be for Case I from three to four years and for Case II it was one to two years.

Residue Theorem based soft sliding mode control for wind power generation systems

This paper proposes a residue theorem based soft sliding mode control strategy for a permanent magnet synchronous generator(PMSG)based wind power generation system(WPGS),to achieve the maximum energy conversion and improved in the system dynamic performance.The main idea is to set a soft dynamic boundary for the controlled variables around a reference point.Thus the controlled variables would lie on a point inside the boundary.The convergence of the operating point is ensured by following the Forward Euler method.The proposed control has been verified via simulation and experiments,compared with conventional sliding mode control(SMC)and proportional integral(PI)control.

Optimal Scheduling Method of Cogeneration System with Heat Storage Device Based on Memetic Algorithm

Electric-heat coupling characteristics of a cogeneration system and the operating mode of fixing electricity with heat are the main reasons for wind abandonment during the heating season in the Three North area.To improve the wind-power absorption capacity and operating economy of the system,the structure of the system is improved by adding a heat storage device and an electric boiler.First,aiming at the minimum operating cost of the system,the optimal scheduling model of the cogeneration system,including a heat storage device and electric boiler,is constructed.Second,according to the characteristics of the problem,a cultural gene algorithm program is compiled to simulate the calculation example.Finally,through the system improvement,the comparison between the conditions before and after and the simulation solutions of similar algorithms prove the effectiveness of the proposed scheme.The simulation results show that adding the heat storage device and electric boiler to the scheduling optimization process not only improves the wind power consumption capacity of the cogeneration system but also reduces the operating cost of the system by significantly reducing the coal consumption of the unit and improving the economy of the system operation.The cultural gene algorithm framework has both the global evolution process of the population and the local search for the characteristics of the problem,which has a better optimization effect on the solution.

A New Cleaner Power Generation System Based on Self-Sustaining Supercritical Water Gasification of Coal

A new cleaner power generation system(IPGS) is proposed and investigated in this paper. Integrating combined cycle with supercritical water gasification of coal, the thermodynamic energy of the produced syngas is cascade utilized according to its temperature and pressure, both sensible and latent heat of the syngas can be recycled into the system, and thereby the net power efficiency can be about 6.4 percentage points higher than that of the traditional GE gasification based power plant(GEPP). The exergy analysis results show that the exergy efficiency of the proposed system reaches 52.45%, which is 13.94% higher than that of the GEPP, and the improvement in exergy efficiency of the proposed system mainly comes from the exergy destruction decline in the syngas energy recovery process, the condensation process and the syngas purification process. The syngas combustion process is the highest exergy destruction process with a value of 157.84 MW in the proposed system. Further performance improvement of the proposed system lies in the utilization process of syngas. Furthermore, system operation parameters have been examined on the coal mass fraction in the supercritical water gasifier(GF), the gasification temperature, and the gasification pressure. The parametric analysis shows that changes in coal concentration in the GF exert more influence on the exergy efficiency of the system compared with the other two parameters.

Effect of Photovoltaic Power Generation on Carbon Dioxide Emission Reduction under Double Carbon Background

Increasing the efficiency and proportion of photovoltaic power generation installations is one of the best ways to reduce both CO_(2) emissions and reliance on fossil-fuel-based power supplies.Solar energy is a clean and renewable power source with excellent potential for further development and utilization.In 2021,the global solar installed capacity was about 749.7 GW.Establishing correlations between solar power generation,standard coal equivalent,carbon sinks,and green sinks is crucial.However,there have been few reports about correlations between the efficiency of tracking solar photovoltaic panels and the above parameters.This paper calculates the increased power generation achievable through the use of tracking photovoltaic panels compared with traditional fixed panels and establishes relationships between power generation,standard coal equivalent,and carbon sinks,providing a basis for attempts to reduce reliance on carbon-based fuels.The calculations show that power generation efficiency can be improved by about 26.12%by enabling solar panels to track the sun's rays during the day and from season to season.Through the use of this improved technology,global CO_(2) emissions can be reduced by 183.63 Mt,and the standard coal equivalent can be reduced by 73.67 Mt yearly.Carbon capture is worth approximately EUR 15.48 billion,and carbon accounting analysis plays a vital role in carbon trading.

Analysis of heat flow diagram of small-scale power generation system:Innovative approaches for improving techno-economic and ecological indices

In this paper,the heat flow diagram of steam turbine model K-6-35 has been analyzed for innovative approaches towards improving the techno-economic and ecological indices of the small-scale power generation system.The numerical analysis is performed using IPSEpro process simulation software based on heat balance method under four different cases.It was found that the study of Solar Assisted Power Generation(SAPG)system has important practical significance in power generation with minimum pollutants and maximum efficiency.Both fuel-saving(FS)and power-boosting(PB)operation modes of the SAPG system are considered.Various types of stand-alone solar thermal power plants exhibited very low overall efficiency with many ecological advantages compared to the conventional thermal power plant based on fossil fuels.Besides,SAPG system with FS mode presented higher techno-economic indices and operation performance.An important reduction in fuel consumption and pollutant emissions could be obtained with SAPG system.Considering the hourly,daily,monthly,and yearly amount of saved fuel and reduced pollutants in the whole power plant,the SAPG system with FS mode can largely contribute to high ecological indices power generation.A thermal efficiency increased by 1.31%with specific equivalent fuel consumption decreased by 22.54 g/kWh was obtained with SAPG system.The coal consumption was reduced by 4.75%when SAPG system operates in FS mode.

Reliability evaluation of tidal and wind power generation system with battery energy storage

This paper presents a method for reliability evaluation of a hybrid generation system of wind and tidal powers with battery energy storage.Such a system may widely exist in coastal areas and islands in the future.A chronological multiple state probability model of tidal power generation system(TPGS)considering both forced outage rate(FOR)of the TPGS and random nature of tidal current speed is developed.In the evaluation of FORs of TPGS and WPGS(wind power generation system),the delivered power related failure rates of power electronic converters for TPGS and WPGS are considered.A chronological power output model of battery energy storage system(BESS)is derived.A hybrid system of tidal and wind generation powers with a BESS is used to demonstrate the effectiveness of the presented method.In case studies,the effects of various parameters on the system reliability are investigated.

Two-Stage Optimal Dispatching of Wind Power-Photovoltaic-Solar Thermal Combined System Considering Economic Optimality and Fairness

Aiming at the problems of large-scale wind and solar grid connection,how to ensure the economy of system operation and how to realize fair scheduling between new energy power stations,a two-stage optimal dispatching model of wind power-photovoltaic-solar thermal combined system considering economic optimality and fairness is proposed.Firstly,the first stage dispatching model takes the overall economy optimization of the system as the goal and the principle of maximizing the consumption of wind and solar output,obtains the optimal output value under the economic conditions of each new energy station,and then obtains the maximum consumption space of the new energy station.Secondly,based on the optimization results of the first stage,the second stage dispatching model uses the dispatching method of fuzzy comprehensive ranking priority to prioritize the new energy stations,and then makes a fair allocation to the dispatching of the wind and solar stations.Finally,the analysis of a specific example shows that themodel can take into account the fairness of active power distribution of new energy stations on the basis of ensuring the economy of system operation,make full use of the consumption space,and realize the medium and long-term fairness distribution of dispatching plan.

Short-Term Prediction of Photovoltaic Power Generation Based on LMD Permutation Entropy and Singular Spectrum Analysis

The power output state of photovoltaic power generation is affected by the earth’s rotation and solar radiation intensity.On the one hand,its output sequence has daily periodicity;on the other hand,it has discrete randomness.With the development of new energy economy,the proportion of photovoltaic energy increased accordingly.In order to solve the problem of improving the energy conversion efficiency in the grid-connected optical network and ensure the stability of photovoltaic power generation,this paper proposes the short-termprediction of photovoltaic power generation based on the improvedmulti-scale permutation entropy,localmean decomposition and singular spectrum analysis algorithm.Firstly,taking the power output per unit day as the research object,the multi-scale permutation entropy is used to calculate the eigenvectors under different weather conditions,and the cluster analysis is used to reconstruct the historical power generation under typical weather rainy and snowy,sunny,abrupt,cloudy.Then,local mean decomposition(LMD)is used to decompose the output sequence,so as to extract more detail components of the reconstructed output sequence.Finally,combined with the weather forecast of the Meteorological Bureau for the next day,the singular spectrumanalysis algorithm is used to predict the photovoltaic classification of the recombination decomposition sequence under typical weather.Through the verification and analysis of examples,the hierarchical prediction experiments of reconstructed and non-reconstructed output sequences are compared.The results show that the algorithm proposed in this paper is effective in realizing the short-term prediction of photovoltaic generator,and has the advantages of simple structure and high prediction accuracy.

New generation traction power supply system and its key technologies for electrified railways

Unlike the traditional traction power supply system which enables the electrified railway traction sub- station to be connected to power grid in a way of phase rotation, a new generation traction power supply system without phase splits is proposed in this paper. Three key techniques used in this system have been discussed. First, a combined co-phase traction power supply system is applied at traction substations for compensating negative sequence current and eliminating phase splits at exits of substations; design method and procedure for this system are presented. Second, a new bilateral traction power supply technology is proposed to eliminate the phase split at section post and reduce the influence of equalizing current on the power grid. Meanwhile, power factor should be adjusted to ensure a proper voltage level of the traction network. Third, a seg- mental power supply technology of traction network is used to divide the power supply arms into several segments, and the synchronous measurement and control technology is applied to diagnose faults and their locations quickly and accurately. Thus, the fault impact can be limited to a min- imum degree. In addition, the economy and reliability of the new generation traction power supply system are analyzed.